{"title":"中国西南岩溶地区生态系统健康的时空演变及其驱动因素","authors":"Ninglei Ouyang, Xiaoping Rui, Xuepeng Zhang, Heng Tang, Yiheng Xie","doi":"10.1016/j.ecolind.2024.112530","DOIUrl":null,"url":null,"abstract":"As one of the most typical karst landscapes globally, the karst regions in southwestern China are characterized by prominent rocky desertification and fragile ecological conditions. Consequently, exploring the spatiotemporal evolution and driving influences on ecosystem health (EH) in this region is of great significance for the improvement of ecosystems and green development. This study focuses on assessing EH in these regions from 2000 to 2020 using the “vitality-organization-recovery-service” (VORS) framework. Spatiotemporal changes in EH are analyzed through hotspot analysis, and the functional relationship between driving factors and EH is quantified using XGBoost and SHAP models. Key findings include: (1) Over the past two decades, the proportion of cities experiencing enhanced EH has generally improved in 73% of cities compared to 27% experiencing deterioration. (2) Spatial analysis reveals EH clustering in three regions. One cold spot cluster in the central north and two hot spot clusters in the southwest and southeast. (3) Urbanization level exhibits an inverse logarithmic relationship with EH. Precipitation affects EH in a cubic polynomial pattern—initial decrease, subsequent increase, and final decrease. Temperature impacts EH through a quartic polynomial function with fluctuating increases and decreases. PM2.5 shows a monotonically decreasing relationship with EH, while the normalized difference vegetation index demonstrates a monotonically increasing association. This research contributes to understanding EH dynamics in southwestern China’s karst landscapes, crucial for advancing ecosystem management and sustainable development efforts.","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":null,"pages":null},"PeriodicalIF":7.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal evolution of ecosystem health and its driving factors in the southwestern karst regions of China\",\"authors\":\"Ninglei Ouyang, Xiaoping Rui, Xuepeng Zhang, Heng Tang, Yiheng Xie\",\"doi\":\"10.1016/j.ecolind.2024.112530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As one of the most typical karst landscapes globally, the karst regions in southwestern China are characterized by prominent rocky desertification and fragile ecological conditions. Consequently, exploring the spatiotemporal evolution and driving influences on ecosystem health (EH) in this region is of great significance for the improvement of ecosystems and green development. This study focuses on assessing EH in these regions from 2000 to 2020 using the “vitality-organization-recovery-service” (VORS) framework. Spatiotemporal changes in EH are analyzed through hotspot analysis, and the functional relationship between driving factors and EH is quantified using XGBoost and SHAP models. Key findings include: (1) Over the past two decades, the proportion of cities experiencing enhanced EH has generally improved in 73% of cities compared to 27% experiencing deterioration. (2) Spatial analysis reveals EH clustering in three regions. One cold spot cluster in the central north and two hot spot clusters in the southwest and southeast. (3) Urbanization level exhibits an inverse logarithmic relationship with EH. Precipitation affects EH in a cubic polynomial pattern—initial decrease, subsequent increase, and final decrease. Temperature impacts EH through a quartic polynomial function with fluctuating increases and decreases. PM2.5 shows a monotonically decreasing relationship with EH, while the normalized difference vegetation index demonstrates a monotonically increasing association. This research contributes to understanding EH dynamics in southwestern China’s karst landscapes, crucial for advancing ecosystem management and sustainable development efforts.\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.ecolind.2024.112530\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.ecolind.2024.112530","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Spatiotemporal evolution of ecosystem health and its driving factors in the southwestern karst regions of China
As one of the most typical karst landscapes globally, the karst regions in southwestern China are characterized by prominent rocky desertification and fragile ecological conditions. Consequently, exploring the spatiotemporal evolution and driving influences on ecosystem health (EH) in this region is of great significance for the improvement of ecosystems and green development. This study focuses on assessing EH in these regions from 2000 to 2020 using the “vitality-organization-recovery-service” (VORS) framework. Spatiotemporal changes in EH are analyzed through hotspot analysis, and the functional relationship between driving factors and EH is quantified using XGBoost and SHAP models. Key findings include: (1) Over the past two decades, the proportion of cities experiencing enhanced EH has generally improved in 73% of cities compared to 27% experiencing deterioration. (2) Spatial analysis reveals EH clustering in three regions. One cold spot cluster in the central north and two hot spot clusters in the southwest and southeast. (3) Urbanization level exhibits an inverse logarithmic relationship with EH. Precipitation affects EH in a cubic polynomial pattern—initial decrease, subsequent increase, and final decrease. Temperature impacts EH through a quartic polynomial function with fluctuating increases and decreases. PM2.5 shows a monotonically decreasing relationship with EH, while the normalized difference vegetation index demonstrates a monotonically increasing association. This research contributes to understanding EH dynamics in southwestern China’s karst landscapes, crucial for advancing ecosystem management and sustainable development efforts.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.